class_docstr: Class write logs to TensorBoard (from TensorFlow).
docstr: Args:
      name: name of metric
      value: float value of metric
      global_step: current step of the training loop
docstr_tok: ["Args",":","name",":","name","of","metric","value",":","float","value","of","metric","global_step",":","current","step","of","the","training","loop"]
code: def log_scalar(self, name: str, value: float, global_step: int):
      """
      Args:
          name: name of metric
          value: float value of metric
          global_step: current step of the training loop
      """
      with self.writer.as_default():
          self.summary.scalar(name, value, step=global_step)
      self.writer.flush()
  
file_path: livelossplot/livelossplot/outputs/tensorboard_tf_logger.py
imports: from datetime import datetime
  from os import path
  from livelossplot.main_logger import MainLogger
  from livelossplot.outputs.base_output import BaseOutput
label_desc: Use image node_id 3 for calling the TensorboardTFLogger obj's underlying member method code with example usage: obj.log_scalar(name, value, global_step) without return types